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Articles 91 - 94 of 94
Full-Text Articles in Engineering
Short-Term Building Energy Model Recommendation System: A Meta-Learning Approach, Can Cui, Teresa Wu, Mengqi Hu, Jeffery D. Weir, Xiwang Li
Short-Term Building Energy Model Recommendation System: A Meta-Learning Approach, Can Cui, Teresa Wu, Mengqi Hu, Jeffery D. Weir, Xiwang Li
Faculty Publications
High-fidelity and computationally efficient energy forecasting models for building systems are needed to ensure optimal automatic operation, reduce energy consumption, and improve the building’s resilience capability to power disturbances. Various models have been developed to forecast building energy consumption. However, given buildings have different characteristics and operating conditions, model performance varies. Existing research has mainly taken a trial-and-error approach by developing multiple models and identifying the best performer for a specific building, or presumed one universal model form which is applied on different building cases. To the best of our knowledge, there does not exist a generalized system framework which …
Unequal A Priori Probability Multiple Hypothesis Testing In Space Domain Awareness With The Space Surveillance Telescope, Tyler J. Hardy, Stephen C. Cain, Travis F. Blake
Unequal A Priori Probability Multiple Hypothesis Testing In Space Domain Awareness With The Space Surveillance Telescope, Tyler J. Hardy, Stephen C. Cain, Travis F. Blake
Faculty Publications
This paper investigates the ability to improve Space Domain Awareness (SDA) by increasing the number of detectable Resident Space Objects (RSOs) from space surveillance sensors. With matched filter based techniques, the expected impulse response, or Point Spread Function (PSF), is compared against the received data. In the situation where the images are spatially undersampled, the modeled PSF may not match the received data if the RSO does not fall in the center of the pixel. This aliasing can be accounted for with a Multiple Hypothesis Test (MHT). Previously, proposed MHTs have implemented a test with an equal a priori prior …
A Recommendation System For Meta-Modeling: A Meta-Learning Based Approach, Can Cui, Mengqi Hu, Jeffery D. Weir, Teresa Wu
A Recommendation System For Meta-Modeling: A Meta-Learning Based Approach, Can Cui, Mengqi Hu, Jeffery D. Weir, Teresa Wu
Faculty Publications
Various meta-modeling techniques have been developed to replace computationally expensive simulation models. The performance of these meta-modeling techniques on different models is varied which makes existing model selection/recommendation approaches (e.g., trial-and-error, ensemble) problematic. To address these research gaps, we propose a general meta-modeling recommendation system using meta-learning which can automate the meta-modeling recommendation process by intelligently adapting the learning bias to problem characterizations. The proposed intelligent recommendation system includes four modules: (1) problem module, (2) meta-feature module which includes a comprehensive set of meta-features to characterize the geometrical properties of problems, (3) meta-learner module which compares the performance of instance-based …
The Influence Of Operational Resources And Activities On Indirect Personnel Costs: A Multilevel Modeling Approach, Bradley C. Boehmke, Alan W. Johnson, Edward D. White, Jeffery D. Weir, Mark A. Gallagher
The Influence Of Operational Resources And Activities On Indirect Personnel Costs: A Multilevel Modeling Approach, Bradley C. Boehmke, Alan W. Johnson, Edward D. White, Jeffery D. Weir, Mark A. Gallagher
Faculty Publications
Indirect activities often represent an underemphasized, yet significant, contributing source of costs for organizations. In order to manage indirect costs, organizations must understand how these costs behave relative to changes in operational resources and activities. This is of particular interest to the Air Force and its sister services, because recent and projected reductions in defense spending are forcing reductions in their operational variables, and insufficient research exists to help them understand how this may influence indirect costs. Furthermore, although academic research on indirect costs has advanced the knowledge behind the modeling and behavior of indirect costs, significant gaps in the …